Journal of Intelligent & Robotic Systems

, Volume 89, Issue 3–4, pp 319–342 | Cite as

Characterisation of Grasp Quality Metrics

  • Carlos RubertEmail author
  • Beatriz León
  • Antonio Morales
  • Joaquín Sancho-Bru


Robot grasp quality metrics are used to evaluate, compare and select robotic grasp configurations. Many of them have been proposed based on a diversity of underlying principles and to assess different aspects of the grasp configurations. As a consequence, some of them provide similar information but other can provide completely different assessments. Combinations of metrics have been proposed in order to provide global indexes, but these attempts have shown the difficulties of merging metrics with different numerical ranges and even physical units. All these studies have raised the need of a deeper knowledge in order to determine independent grasp quality metrics which enable a global assessment of a grasp, and a way to combine them. This paper presents an exhaustive study in order to provide numerical evidence for these issues. Ten quality metrics are used to evaluate a set of grasps planned by a simulator for 7 different robot hands over a set of 126 object models. Three statistical analysis, namely, variability, correlation and sensitivity, are performed over this extensive database. Results and graphs presented allow to set practical thresholds for each quality metric, select independent metrics, and determine the robustness of each metric,providing a reliability indicator under pose uncertainty. The results from this paper are intended to serve as guidance for practical use of quality metrics by researchers on grasp planning algorithms.


Grasp planning Multifingered hands Quality metrics 


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This research was partly supported by Ministerio de Educación, Ciencia y Tecnología (Grant No. R31 - 2008 - 000 - 10062 - 0), by Ministerio de Ciencia e Innovación (DPI2011 - 27846), by Ministerio de Economía y Competitividad (DPI2014 - 60635 - R) by Generalitat Valenciana (PROMETEO/2009/052, PROMETEOII/2014/028 ) and by Fundació Caixa Castelló-Bancaixa (P1 - 1B2011 - 54 and PI - 1B2011 - 25).


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Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  1. 1.Robotic Intelligence Laboratory at the Department of Computer Science and EngineeringUniversitat Jaume ICastellónSpain
  2. 2.Group of Biomechanics and Ergonomics at the Department of Mechanical Engineering and ConstructionUniversitat Jaume ICastellónSpain

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